A light-field contains all the spatial and angular visual information of a scene and can enable various applications. However, the four-dimensional (4D) nature of the light-field significantly increases data size. In order to enable projection of the light-field data to generate final two-dimensional (2D) images of sufficient quality, the required size of the light-field is usually orders of magnitude larger than that of a 2D image. Therefore, high-performance light-field compression is a crucial technique for the light-field processing system.
In theory, the light-field data is highly redundant and compressible. However, in practice, it is difficult to exploit those redundancies properly from such a high-dimensional signal. Furthermore, the light-field captured by most light-field cameras is often irregularly sampled and highly aliased. Application of traditional image/video compression techniques to compress light-field data often yields unsatisfactory results. One key problem is that existing techniques generally assume the input data is band-limited and has strong correlation in the spatial or frequency domain, but these assumptions do not generally hold true of real light-field data.